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Folia Morphol (Warsz). 2019 Apr 17. doi: 10.5603/FM.a2019.0045. [Epub ahead of print]

Semi-automatic segmentation and surface reconstruction of CT images by using rotoscoping and warping techniques.

Author information

1
Department of Emergency Medical Technology, Gachon University of College of Health Science, 119 Hambakmoe-ro, Yeonsu-gu, Incheon 406-799, South Korea, incheon, Korea, Republic Of.
2
Department of Emergency Medical Technology, Gachon University of College of Health Science, 119 Hambakmoe-ro, Yeonsu-gu, Incheon 406-799, South Korea, incheon, Korea, Republic Of. sdssoft@gmail.com.

Abstract

BACKGROUND:

Quick and large-scale segmentation along with three-dimensional (3D) reconstruction is necessary to make precise 3D musculoskeletal models for surface anatomy education, palpation training, medical communication, morphology research, and virtual surgery simulation. However, automatic segmentation of the skin and muscles remain undeveloped.

MATERIALS AND METHODS:

Therefore, in this study, we developed workflows for semi-automatic segmentation and surface reconstruction, using rotoscoping and warping techniques.

RESULTS:

The techniques were applied to multi detector computed tomography images, which were optimized to quickly generate surface models of the skin and the anatomical structures underlying the fat tissue.

CONCLUSIONS:

The workflows developed in this study are expected to enable researchers to create segmented images and optimized surface models from any set of serially sectioned images quickly and conveniently. Moreover, these optimized surface models can easily be modified for further application or educational use.

KEYWORDS:

cross-sectional anatomy; landmark; rotoscoping; segmentation; surface anatomy; surface reconstruction; three-dimensional imaging

PMID:
30993664
DOI:
10.5603/FM.a2019.0045
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